In [11]:
df_salary = df[c0 & c1 & c2 & c3 & c4 & c5 & c6 & c7n]
salary = df_salary['Salary band'].unique().tolist()
count_salary = pd.pivot_table(df_salary, values='Number',index='Salary band', aggfunc='sum')
count_salary_reset = count_salary.reset_index()
color_map = ['#20639B' for _ in range(14)]
color_map[4] = '#ED553B' # color highlight
# initialize the figure
plt.figure(figsize=(8,8),dpi=200)
ax = plt.subplot(111, polar=True)
plt.axis('off')
# Constants = parameters controling the plot layout:
upperLimit = 20
lowerLimit = 1
labelPadding = 20
# Compute max and min in the dataset
max = count_salary_reset['Number'].max()
# Let's compute heights: they are a conversion of each item value in those new coordinates
# In our example, 0 in the dataset will be converted to the lowerLimit (10)
# The maximum will be converted to the upperLimit (100)
slope = (max - lowerLimit) / max
heights = slope * count_salary_reset.Number + lowerLimit
# Compute the width of each bar. In total we have 2*Pi = 360°
width = 2*np.pi / len(count_salary_reset.index)
# Compute the angle each bar is centered on:
indexes = list(range(1, len(count_salary_reset.index)+1))
angles = [element * width for element in indexes]
angles
# Draw bars
bars = ax.bar(
x=angles,
height=heights,
width=width,
bottom=lowerLimit,
linewidth=2,
edgecolor="white",
color=color_map,alpha=0.8
)
# Add labels
for bar, angle, height, label in zip(bars,angles, heights, count_salary_reset["Salary band"]):
# Labels are rotated. Rotation must be specified in degrees :(
rotation = np.rad2deg(angle)
# Flip some labels upside down
alignment = ""
if angle >= np.pi/2 and angle < 3*np.pi/2:
alignment = "right"
rotation = rotation + 180
else:
alignment = "left"
# Finally add the labels
ax.text(
x=angle,
y=lowerLimit + bar.get_height() + labelPadding,
s=label,
ha=alignment, fontsize=6,fontfamily='serif',
va='center',
rotation=rotation,
rotation_mode="anchor")
